{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c8d01073-09a8-4c68-b93b-aef463738bd0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:52:47.063503Z",
     "iopub.status.busy": "2022-07-07T01:52:47.063331Z",
     "iopub.status.idle": "2022-07-07T01:52:48.403198Z",
     "shell.execute_reply": "2022-07-07T01:52:48.402664Z",
     "shell.execute_reply.started": "2022-07-07T01:52:47.063487Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "import os, sys, glob, argparse\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "\n",
    "%pylab inline\n",
    "\n",
    "import cv2\n",
    "from PIL import Image\n",
    "from sklearn.model_selection import train_test_split, StratifiedKFold, KFold\n",
    "\n",
    "import torch\n",
    "torch.manual_seed(0)\n",
    "torch.backends.cudnn.deterministic = False\n",
    "torch.backends.cudnn.benchmark = True\n",
    "\n",
    "import torchvision.models as models\n",
    "import torchvision.transforms as transforms\n",
    "import torchvision.datasets as datasets\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import torch.optim as optim\n",
    "from torch.autograd import Variable\n",
    "from torch.utils.data.dataset import Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "431a9196-30ec-4f86-8da7-cd6e2edc7154",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:52:48.404300Z",
     "iopub.status.busy": "2022-07-07T01:52:48.404073Z",
     "iopub.status.idle": "2022-07-07T01:52:48.414248Z",
     "shell.execute_reply": "2022-07-07T01:52:48.413828Z",
     "shell.execute_reply.started": "2022-07-07T01:52:48.404284Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "train_df = pd.read_csv('./智能硬件语音控制的时频图分类挑战赛公开数据/train.csv')\n",
    "train_df['path'] = './智能硬件语音控制的时频图分类挑战赛公开数据/train/' + train_df['image']\n",
    "# np.random.shuffle(train_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c46e81d0-b02b-4982-84c4-2b53b6d76101",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:52:48.415049Z",
     "iopub.status.busy": "2022-07-07T01:52:48.414883Z",
     "iopub.status.idle": "2022-07-07T01:52:48.631953Z",
     "shell.execute_reply": "2022-07-07T01:52:48.631512Z",
     "shell.execute_reply.started": "2022-07-07T01:52:48.415034Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fb44e9a9198>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(cv2.imread(train_df['path'].iloc[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8cf398db-d606-493f-b942-8e8d717e1b4a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:52:48.632781Z",
     "iopub.status.busy": "2022-07-07T01:52:48.632612Z",
     "iopub.status.idle": "2022-07-07T01:52:48.637357Z",
     "shell.execute_reply": "2022-07-07T01:52:48.636987Z",
     "shell.execute_reply.started": "2022-07-07T01:52:48.632765Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "test_df = pd.read_csv('智能硬件语音控制的时频图分类挑战赛公开数据/提交示例.csv')\n",
    "test_df['path'] = '智能硬件语音控制的时频图分类挑战赛公开数据/test/' + test_df['image'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "584f2188-cf45-4d72-abee-4dae0d362926",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:52:48.638469Z",
     "iopub.status.busy": "2022-07-07T01:52:48.638306Z",
     "iopub.status.idle": "2022-07-07T01:52:48.701750Z",
     "shell.execute_reply": "2022-07-07T01:52:48.701258Z",
     "shell.execute_reply.started": "2022-07-07T01:52:48.638455Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "class XunFeiDataset(Dataset):\n",
    "    def __init__(self, img_path, label, transform=None):\n",
    "        self.img_path = img_path\n",
    "        self.label = label\n",
    "        if transform is not None:\n",
    "            self.transform = transform\n",
    "        else:\n",
    "            self.transform = None\n",
    "    \n",
    "    def __getitem__(self, index):\n",
    "        img = cv2.imread(self.img_path[index])            \n",
    "        img = img.astype(np.float32)\n",
    "        \n",
    "        img /= 255.0\n",
    "        img -= 1\n",
    "        \n",
    "        if self.transform is not None:\n",
    "            img = self.transform(image = img)['image']\n",
    "        img = img.transpose([2,0,1])\n",
    "        \n",
    "        return img,torch.from_numpy(np.array(self.label[index]))\n",
    "    \n",
    "    def __len__(self):\n",
    "        return len(self.img_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bd5a22b6-3a32-4039-bcc7-a6c6f5f9cbaf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:52:48.702906Z",
     "iopub.status.busy": "2022-07-07T01:52:48.702602Z",
     "iopub.status.idle": "2022-07-07T01:52:48.764139Z",
     "shell.execute_reply": "2022-07-07T01:52:48.763025Z",
     "shell.execute_reply.started": "2022-07-07T01:52:48.702887Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "class XunFeiNet(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(XunFeiNet, self).__init__()\n",
    "                \n",
    "        model = models.resnet18(True)\n",
    "        model.avgpool = nn.AdaptiveAvgPool2d(1)\n",
    "        model.fc = nn.Linear(512, 24)\n",
    "        self.resnet = model\n",
    "        \n",
    "    def forward(self, img):        \n",
    "        out = self.resnet(img)\n",
    "        return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "47539bef-14a7-4881-85e9-0882ff295e6a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:52:48.766277Z",
     "iopub.status.busy": "2022-07-07T01:52:48.765799Z",
     "iopub.status.idle": "2022-07-07T01:52:48.842236Z",
     "shell.execute_reply": "2022-07-07T01:52:48.841635Z",
     "shell.execute_reply.started": "2022-07-07T01:52:48.766234Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def train(train_loader, model, criterion, optimizer):\n",
    "    model.train()\n",
    "    train_loss = 0.0\n",
    "    for i, (input, target) in enumerate(train_loader):\n",
    "        input = input.cuda(non_blocking=True)\n",
    "        target = target.cuda(non_blocking=True)\n",
    "\n",
    "        # compute output\n",
    "        output = model(input)\n",
    "        loss = criterion(output, target)\n",
    "\n",
    "        # compute gradient and do SGD step\n",
    "        optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "\n",
    "        if i % 40 == 0:\n",
    "            print(loss.item())\n",
    "            \n",
    "        train_loss += loss.item()\n",
    "    \n",
    "    return train_loss/len(train_loader)\n",
    "            \n",
    "def validate(val_loader, model, criterion):\n",
    "    model.eval()\n",
    "    \n",
    "    val_acc = 0.0\n",
    "    \n",
    "    with torch.no_grad():\n",
    "        end = time.time()\n",
    "        for i, (input, target) in enumerate(val_loader):\n",
    "            input = input.cuda()\n",
    "            target = target.cuda()\n",
    "\n",
    "            # compute output\n",
    "            output = model(input)\n",
    "            loss = criterion(output, target)\n",
    "            \n",
    "            val_acc += (output.argmax(1) == target).sum().item()\n",
    "            \n",
    "    return val_acc / len(val_loader.dataset)\n",
    "\n",
    "def predict(test_loader, model, criterion):\n",
    "    model.eval()\n",
    "    val_acc = 0.0\n",
    "    \n",
    "    test_pred = []\n",
    "    with torch.no_grad():\n",
    "        end = time.time()\n",
    "        for i, (input, target) in enumerate(test_loader):\n",
    "            input = input.cuda()\n",
    "            target = target.cuda()\n",
    "\n",
    "            # compute output\n",
    "            output = model(input)\n",
    "            test_pred.append(output.data.cpu().numpy())\n",
    "            \n",
    "    return np.vstack(test_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c14b410f-de94-4f52-be5b-1377c34bda4a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:52:48.843123Z",
     "iopub.status.busy": "2022-07-07T01:52:48.842928Z",
     "iopub.status.idle": "2022-07-07T01:52:49.079245Z",
     "shell.execute_reply": "2022-07-07T01:52:49.078667Z",
     "shell.execute_reply.started": "2022-07-07T01:52:48.843107Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import albumentations as A\n",
    "\n",
    "train_loader = torch.utils.data.DataLoader(\n",
    "    XunFeiDataset(train_df['path'].values[:-200], train_df['label'].values[:-200],\n",
    "            A.Compose([\n",
    "            # A.Resize(300, 300),\n",
    "            A.RandomCrop(450, 750),\n",
    "            # A.HorizontalFlip(p=0.5),\n",
    "            # A.RandomContrast(p=0.5),\n",
    "            # A.RandomBrightnessContrast(p=0.5),\n",
    "        ])\n",
    "    ), batch_size=5, shuffle=True, num_workers=1, pin_memory=False\n",
    ")\n",
    "\n",
    "val_loader = torch.utils.data.DataLoader(\n",
    "    XunFeiDataset(train_df['path'].values[-200:], train_df['label'].values[-200:],\n",
    "            A.Compose([\n",
    "            # A.Resize(300, 300),\n",
    "            A.RandomCrop(450, 750),\n",
    "            # A.HorizontalFlip(p=0.5),\n",
    "            # A.RandomContrast(p=0.5),\n",
    "        ])\n",
    "    ), batch_size=2, shuffle=False, num_workers=1, pin_memory=False\n",
    ")\n",
    "\n",
    "# test_loader = torch.utils.data.DataLoader(\n",
    "#     XunFeiDataset(test_df['path'].values,\n",
    "#             A.Compose([\n",
    "#             # A.Resize(300, 300),\n",
    "#             A.RandomCrop(130, 450),\n",
    "#             # A.HorizontalFlip(p=0.5),\n",
    "#             # A.RandomContrast(p=0.5),\n",
    "#         ])\n",
    "#     ), batch_size=10, shuffle=False, num_workers=1, pin_memory=False\n",
    "# )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7f7ee8cb-cfc0-4eb8-96ea-7302144ae7a4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:52:49.080133Z",
     "iopub.status.busy": "2022-07-07T01:52:49.079931Z",
     "iopub.status.idle": "2022-07-07T01:52:50.963091Z",
     "shell.execute_reply": "2022-07-07T01:52:50.962554Z",
     "shell.execute_reply.started": "2022-07-07T01:52:49.080117Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "model = XunFeiNet()\n",
    "model = model.to('cuda')\n",
    "criterion = nn.CrossEntropyLoss().cuda()\n",
    "optimizer = torch.optim.Adam(model.parameters(), 0.001)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b2faad78-e794-4f31-8b56-1a64dbf89ccc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:52:50.964044Z",
     "iopub.status.busy": "2022-07-07T01:52:50.963877Z",
     "iopub.status.idle": "2022-07-07T01:57:12.682020Z",
     "shell.execute_reply": "2022-07-07T01:57:12.681456Z",
     "shell.execute_reply.started": "2022-07-07T01:52:50.964029Z"
    },
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.2952709197998047\n",
      "3.5732827186584473\n",
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      "3.0097222328186035\n",
      "3.2620487403134146 0.06\n",
      "3.102877140045166\n",
      "2.9085853099823\n",
      "3.382877826690674\n",
      "3.265240430831909\n",
      "3.0676724910736084\n",
      "3.2301926612854004\n",
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      "2.991442918777466\n",
      "3.039703607559204\n",
      "3.2347688962990335 0.045\n",
      "3.1707894802093506\n",
      "2.871647357940674\n",
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      "3.1578618517878123 0.06\n",
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      "2.2580342292785645\n",
      "1.8755404949188232\n",
      "1.9908361969692847 0.37\n",
      "1.2829139232635498\n",
      "3.4123306274414062\n",
      "1.840044617652893\n",
      "1.2839382886886597\n",
      "1.3441885709762573\n",
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      "1.8374271392822266\n",
      "1.2042092084884644\n",
      "0.8777147531509399\n",
      "1.9511638879776\n",
      "1.5594445949654958 0.45\n"
     ]
    }
   ],
   "source": [
    "for _  in range(20):\n",
    "    train_loss = train(train_loader, model, criterion, optimizer)\n",
    "    val_acc = validate(val_loader, model, criterion)\n",
    "    \n",
    "    print(train_loss, val_acc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6787d12a-b923-4777-abf5-4d90904551d1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:57:12.683268Z",
     "iopub.status.busy": "2022-07-07T01:57:12.683039Z",
     "iopub.status.idle": "2022-07-07T01:57:50.315824Z",
     "shell.execute_reply": "2022-07-07T01:57:50.314768Z",
     "shell.execute_reply.started": "2022-07-07T01:57:12.683245Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "test_loader = torch.utils.data.DataLoader(\n",
    "    XunFeiDataset(test_df['path'].values, [0] * test_df.shape[0],\n",
    "            A.Compose([\n",
    "            # A.Resize(300, 300),\n",
    "            A.RandomCrop(450, 750),\n",
    "            # A.HorizontalFlip(p=0.5),\n",
    "            # A.RandomContrast(p=0.5),\n",
    "        ])\n",
    "    ), batch_size=10, shuffle=False, num_workers=1, pin_memory=False\n",
    ")\n",
    "\n",
    "pred = None\n",
    "\n",
    "for _ in range(5):\n",
    "    if pred is None:\n",
    "        pred = predict(test_loader, model, criterion)\n",
    "    else:\n",
    "        pred += predict(test_loader, model, criterion)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e85ebd1a-6bfa-40b2-a948-2e0c3c348861",
   "metadata": {},
   "source": [
    "# Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1743990f-d27d-43cd-85fd-23a0ff0f2c36",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:57:50.316883Z",
     "iopub.status.busy": "2022-07-07T01:57:50.316673Z",
     "iopub.status.idle": "2022-07-07T01:57:50.321145Z",
     "shell.execute_reply": "2022-07-07T01:57:50.320711Z",
     "shell.execute_reply.started": "2022-07-07T01:57:50.316865Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "submit = pd.DataFrame(\n",
    "    {\n",
    "        'image': [x.split('/')[-1] for x in test_df['path'].values],\n",
    "        'label': pred.argmax(1)\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "cc565971-7a5f-4bb0-8ab5-c33281bc469c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:57:50.322048Z",
     "iopub.status.busy": "2022-07-07T01:57:50.321842Z",
     "iopub.status.idle": "2022-07-07T01:57:50.472339Z",
     "shell.execute_reply": "2022-07-07T01:57:50.471302Z",
     "shell.execute_reply.started": "2022-07-07T01:57:50.322034Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# test_df = pd.read_csv('提交示例.csv')\n",
    "# test_df['label'] = pred.argmax(1)\n",
    "\n",
    "# submit = submit.sort_values(by='id')\n",
    "# test_df.to_csv('submit2.csv', index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "129ff32f-8444-4cf2-9997-0101960ea490",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-07T01:57:50.474657Z",
     "iopub.status.busy": "2022-07-07T01:57:50.474083Z",
     "iopub.status.idle": "2022-07-07T01:57:50.538895Z",
     "shell.execute_reply": "2022-07-07T01:57:50.538245Z",
     "shell.execute_reply.started": "2022-07-07T01:57:50.474611Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "submit.to_csv('sub.csv', index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7cc02306-d27d-4b5c-a6c5-1777ef71bda8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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  "language_info": {
   "codemirror_mode": {
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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